Efficient Calibration of Radio Interferometers Using Block LDU Decomposition. Sardarabadi, A. M., van der Veen , A., & Koopmans, L. V. E. In *2018 26th European Signal Processing Conference (EUSIPCO)*, pages 2688-2692, Sep., 2018.

Paper doi abstract bibtex

Paper doi abstract bibtex

Having an accurate calibration method is crucial for any scientific research done by a radio telescope. The next generation radio telescopes such as the Square Kilometre Array (SKA) will have a large number of receivers which will produce exabytes of data per day. In this paper we propose new direction-dependent and independent calibration algorithms that, while requiring much less storage during calibration, converge very fast. The calibration problem can be formulated as a non-linear least square optimization problem. We show that combining a block-LDU decomposition with Gauss-Newton iterations produces systems of equations with convergent matrices. This allows significant reduction in complexity per iteration and very fast converging algorithms. We also discuss extensions to direction-dependent calibration. The proposed algorithms are evaluated using simulations.

@InProceedings{8553058, author = {A. M. Sardarabadi and A. {van der Veen} and L. V. E. Koopmans}, booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)}, title = {Efficient Calibration of Radio Interferometers Using Block LDU Decomposition}, year = {2018}, pages = {2688-2692}, abstract = {Having an accurate calibration method is crucial for any scientific research done by a radio telescope. The next generation radio telescopes such as the Square Kilometre Array (SKA) will have a large number of receivers which will produce exabytes of data per day. In this paper we propose new direction-dependent and independent calibration algorithms that, while requiring much less storage during calibration, converge very fast. The calibration problem can be formulated as a non-linear least square optimization problem. We show that combining a block-LDU decomposition with Gauss-Newton iterations produces systems of equations with convergent matrices. This allows significant reduction in complexity per iteration and very fast converging algorithms. We also discuss extensions to direction-dependent calibration. The proposed algorithms are evaluated using simulations.}, keywords = {calibration;iterative methods;least squares approximations;matrix algebra;Newton method;optimisation;radiotelescopes;accurate calibration method;scientific research;radio telescope;generation radio;Square Kilometre Array;independent calibration algorithms;nonlinear least square optimization problem;block-LDU decomposition;Gauss-Newton iterations;convergent matrices;direction-dependent calibration;radio interferometers;block LDU decomposition;Calibration;Covariance matrices;Receivers;Mathematical model;Data models;Signal processing algorithms;Radio astronomy;Calibration;Radio Astronomy;Non-Linear Optimization;Covariance Matching}, doi = {10.23919/EUSIPCO.2018.8553058}, issn = {2076-1465}, month = {Sep.}, url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570438736.pdf}, }

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